publication . Conference object . 2021

Efficient Exact Computation of Setwise Minimax Regret for Interactive Preference Elicitation

Toffano, Federico; Viappiani, Paolo; Wilson, Nic,;
English
  • Published: 03 May 2021
  • Publisher: HAL CCSD
  • Country: France
Abstract
International audience; A key issue in artificial intelligence methods for interactive preference elicitation is choosing at each stage an appropriate query to the user, in order to find a near-optimal solution as quickly as possible. A theoretically attractive method is to choose a query that minimises max setwise regret (which corresponds to the worst case loss response in terms of value of information). We focus here on the situation in which the choices are represented explicitly in a database, and with a model of user utility as a weighted sum of the criteria; in this case when the user makes a choice, an agent learns a linear constraint on the unknown vect...
Subjects
free text keywords: Interactive Preference Elicitation, Setwise Minimax Regret, Human-Agent Interaction, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Related Organizations
Funded by
SFI| INSIGHT - Irelands Big Data and Analytics Research Centre
Project
  • Funder: Science Foundation Ireland (SFI)
  • Project Code: 12/RC/2289
  • Funding stream: SFI Research Centres
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